Corresponding author: Nermin Kajtazovic ( nermin.kajtazovic@siemens.com ) © Nermin Kajtazovic, Peter Hödl, Leo Happ Botler. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY-ND 4.0). This license allows reusers to copy and distribute the material in any medium or format in unadapted form only, and only so long as attribution is given to the creator. The license allows for commercial use. Citation:
Kajtazovic N, Hödl P, Botler LH (2021) A Compiler and Language Support for Designing Mixed-Criticality Applications. JUCS - Journal of Universal Computer Science 27(8): 894-911. https://doi.org/10.3897/jucs.71831 |
Coexistence of software components and functions of different criticality in a single computing platform has challenged the safety community for the past two decades. Despite efforts that have been made so far, dealing with mixed-criticality has still left some room for improvements. One particular concern here is that partitioning of hardware and software resources with regard to criticality (safety related, non-safety related) has direct implications on how safety measures need to be realised. For example, a self-test that must meet certain diagnostic coverage for the microcontroller core by inspecting its instructions, needs to cover only those instructions which are able to affect a safety function. Available software mechanisms and tools are to a certain extent still unable to deal with such a fine-grained selection of resources. In this work, we introduce a compiler extension and language support which enable accurate selection of data based on their criticality. The compiler extension serves to establish detailed traceability between the software code and its representation in runtime memory. With the language support, the individual data elements can be classified based on the desired safety integrity level. As a result, safety measures that operate on data (e.g. Abraham test for SRAM can achieve better coverage. The method has been evaluated and applied to industrial safety controllers. We provide here relevant performance figures and discuss possible applications of the method in other fields.